get_product
Get detailed information about a specific grocery product by its ID. Product IDs are returned in search results.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | Product ID from search results |
Get detailed information about a specific grocery product by its ID. Product IDs are returned in search results.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | Product ID from search results |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden. It clearly implies a read-only operation ('Get') with no side effects, but does not disclose behavior on invalid IDs, required permissions, or return format. For a simple retrieval tool, this is adequate but lacks richness.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action, and every phrase is necessary. It avoids redundancy with the schema aside from the note about product IDs, which is concise and helpful as usage guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description adequately covers what it does and where the input comes from. It could mention what fields 'detailed information' includes, but the essential context is present for an agent to select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with a description for product_id ('Product ID from search results'). The tool description repeats this same information ('Product IDs are returned in search results') without adding new meaning, so it does not elevate beyond the baseline for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get detailed information about a specific grocery product by its ID.' This uses a specific verb ('Get') and resource ('grocery product'), and distinguishes it from sibling tools like search_products by emphasizing retrieval of a single product by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context by noting that 'Product IDs are returned in search results,' implying the tool should be used after a search to fetch details. While it doesn't explicitly name alternatives or exclusions, the guidance is sufficient for an agent to sequence search_products then get_product.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
batch_search, search_products, and get_cheapest all provide product search with overlapping output, and build_basket/save_basket both handle basket creation. However, detailed usage notes (mandatory vs. advanced) help clarify, though an agent could still misselect among the search tools.
All tools follow a consistent verb_noun pattern in lowercase_snake_case (e.g., batch_search, compare_prices, get_product), making the API predictable and easy to learn.
10 tools is well within the ideal 3-15 range and appropriately scoped for a grocery price-comparison and basket-building service, covering search, comparison, history, specials, and basket workflows without redundancy.
The tool set covers the full grocery shopping lifecycle: searching products, comparing prices by barcode, viewing price history, checking specials, building baskets, and saving manually curated selections. No obvious gaps for typical user requests.